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The ordinary fixes—the kind that draw on people’s will, and require eating less and moving more—rarely have a large or lasting effect. Indeed, America itself has suffered through a long, maddening history of failed attempts to change its habits on a national scale: a yo-yo diet of well-intentioned treatments, policies, and other social interventions that only ever lead us back to where we started

Through it all, obesity rates keep going up; the diabetes epidemic keeps worsening.

The most recent miracle, for Barb as well as for the nation, has come in the form of injectable drugs. In early 2021, the Danish pharmaceutical company Novo Nordisk published a clinical trial showing remarkable results for semaglutide, now sold under the trade names Wegovy and Ozempic.

Patients in the study who’d had injections of the drug lost, on average, close to 15 percent of their body weight—more than had ever been achieved with any other drug in a study of that size. Wadden knew immediately that this would be “an incredible revolution in the treatment of obesity.”

Many more drugs are now racing through development: survodutide, pemvidutide, retatrutide. (Among specialists, that last one has produced the most excitement: An early trial found an average weight loss of 24 percent in one group of participants.

In the United States, an estimated 189 million adults are classified as having obesity or being overweight

The drugs don’t work for everyone. Their major side effects—nausea, vomiting, and diarrhea—can be too intense for many patients. Others don’t end up losing any weight

For the time being, just 25 percent of private insurers offer the relevant coverage, and the cost of treatment—about $1,000 a month—has been prohibitive for many Americans.

The drugs have already been approved not just for people with diabetes or obesity, but for anyone who has a BMI of more than 27 and an associated health condition, such as high blood pressure or cholesterol. By those criteria, more than 140 million American adults already qualify

if this story goes the way it’s gone for other “risk factor” drugs such as statins and antihypertensives, then the threshold for prescriptions will be lowered over time, inching further toward the weight range we now describe as “normal.”

How you view that prospect will depend on your attitudes about obesity, and your tolerance for risk

The first GLP-1 drug to receive FDA approval, exenatide, has been used as a diabetes treatment for more than 20 years. No long-term harms have been identified—but then again, that drug’s long-term effects have been studied carefully only across a span of seven years

the data so far look very good. “These are now being used, literally, in hundreds of thousands of people across the world,” she told me, and although some studies have suggested that GLP-1 drugs may cause inflammation of the pancreas, or even tumor growth, these concerns have not borne out.

adolescents are injecting newer versions of these drugs, and may continue to do so every week for 50 years or more. What might happen over all that time?

“All of us, in the back of our minds, always wonder, Will something show up?  ” Although no serious problems have yet emerged, she said, “you wonder, and you worry.”

in light of what we’ve been through, it’s hard to see what other choices still remain. For 40 years, we’ve tried to curb the spread of obesity and its related ailments, and for 40 years, we’ve failed. We don’t know how to fix the problem. We don’t even understand what’s really causing it. Now, again, we have a new approach. This time around, the fix had better work.

The fen-phen revolution arrived at a crucial turning point for Wadden’s field, and indeed for his career. By then he’d spent almost 15 years at the leading edge of research into dietary interventions, seeing how much weight a person might lose through careful cutting of their calories.

But that sort of diet science—and the diet culture that it helped support—had lately come into a state of ruin. Americans were fatter than they’d ever been, and they were giving up on losing weight. According to one industry group, the total number of dieters in the country declined by more than 25 percent from 1986 to 1991.

Rejecting diet culture became something of a feminist cause. “A growing number of women are joining in an anti-diet movement,” The New York Times reported in 1992. “They are forming support groups and ceasing to diet with a resolve similar to that of secretaries who 20 years ago stopped getting coffee for their bosses.

Now Wadden and other obesity researchers were reaching a consensus that behavioral interventions might produce in the very best scenario an average lasting weight loss of just 5 to 10 percent

National surveys completed in 1994 showed that the adult obesity rate had surged by more than half since 1980, while the proportion of children classified as overweight had doubled. The need for weight control in America had never seemed so great, even as the chances of achieving it were never perceived to be so small.

Wadden wasn’t terribly concerned, because no one in his study had reported any heart symptoms. But ultrasounds revealed that nearly one-third of them had some degree of leakage in their heart valves. His “cure for obesity” was in fact a source of harm.

In December 1994, the Times ran an editorial on what was understood to be a pivotal discovery: A genetic basis for obesity had finally been found. Researchers at Rockefeller University were investigating a molecule, later named leptin, that gets secreted from fat cells and travels to the brain, and that causes feelings of satiety. Lab mice with mutations in the leptin gene—importantly, a gene also found in humans—overeat until they’re three times the size of other mice. “The finding holds out the dazzling hope,”

In April 1996, the doctors recommended yes: Dexfenfluramine was approved—and became an instant blockbuster. Patients received prescriptions by the hundreds of thousands every month. Sketchy wellness clinics—call toll-free, 1-888-4FEN-FEN—helped meet demand. Then, as now, experts voiced concerns about access. Then, as now, they worried that people who didn’t really need the drugs were lining up to take them. By the end of the year, sales of “fen” alone had surpassed $300 million.

It was nothing less than an awakening, for doctors and their patients alike. Now a patient could be treated for excess weight in the same way they might be treated for diabetes or hypertension—with a drug they’d have to take for the rest of their life.

the article heralded a “new understanding of obesity as a chronic disease rather than a failure of willpower.”

News had just come out that, at the Mayo Clinic in Minnesota, two dozen women taking fen-phen—including six who were, like Barb, in their 30s—had developed cardiac conditions. A few had needed surgery, and on the operating table, doctors discovered that their heart valves were covered with a waxy plaque.

Americans had been prescribed regular fenfluramine since 1973, and the newer drug, dexfenfluramine, had been available in France since 1985. Experts took comfort in this history. Using language that is familiar from today’s assurances regarding semaglutide and other GLP-1 drugs, they pointed out that millions were already on the medication. “It is highly unlikely that there is anything significant in toxicity to the drug that hasn’t been picked up with this kind of experience,” an FDA official named James Bilstad would later say in a Time cover story headlined “The Hot New Diet Pill.

“I know I can’t get any more,” she told Williams. “I have to use up what I have. And then I don’t know what I’m going to do after that. That’s the problem—and that is what scares me to death.” Telling people to lose weight the “natural way,” she told another guest, who was suggesting that people with obesity need only go on low-carb diets, is like “asking a person with a thyroid condition to just stop their medication.”

She’d gone off the fen-phen and had rapidly regained weight. “The voices returned and came back in a furor I’d never heard before,” Barb later wrote on her blog. “It was as if they were so angry at being silenced for so long, they were going to tell me 19 months’ worth of what they wanted me to hear. I was forced to listen. And I ate. And I ate. And ate.”

For Barb, rapid weight loss has brought on a different metaphysical confusion. When she looks in the mirror, she sometimes sees her shape as it was two years ago. In certain corners of the internet, this is known as “phantom fat syndrome,” but Barb dislikes that term. She thinks it should be called “body integration syndrome,” stemming from a disconnect between your “larger-body memory” and “smaller-body reality.

In 2003, the U.S. surgeon general declared obesity “the terror within, a threat that is every bit as real to America as the weapons of mass destruction”; a few months later, Eric Finkelstein, an economist who studies the social costs of obesity, put out an influential paper finding that excess weight was associated with up to $79 billion in health-care spending in 1998, of which roughly half was paid by Medicare and Medicaid. (Later he’d conclude that the number had nearly doubled in a decade.

In 2004, Finkelstein attended an Action on Obesity summit hosted by the Mayo Clinic, at which numerous social interventions were proposed, including calorie labeling in workplace cafeterias and mandatory gym class for children of all grades.

he message at their core, that soda was a form of poison like tobacco, spread. In San Francisco and New York, public-service campaigns showed images of soda bottles pouring out a stream of glistening, blood-streaked fat. Michelle Obama led an effort to depict water—plain old water—as something “cool” to drink.

Soon, the federal government took up many of the ideas that Brownell had helped popularize. Barack Obama had promised while campaigning for president that if America’s obesity trends could be reversed, the Medicare system alone would save “a trillion dollars.” By fighting fat, he implied, his ambitious plan for health-care reform would pay for itself. Once he was in office, his administration pulled every policy lever it could.

Michelle Obama helped guide these efforts, working with marketing experts to develop ways of nudging kids toward better diets and pledging to eliminate “food deserts,” or neighborhoods that lacked convenient access to healthy, affordable food. She was relentless in her public messaging; she planted an organic garden at the White House and promoted her signature “Let’s Move!” campaign around the country.

An all-out war on soda would come to stand in for these broad efforts. Nutrition studies found that half of all Americans were drinking sugar-sweetened beverages every day, and that consumption of these accounted for one-third of the added sugar in adults’ diets. Studies turned up links between people’s soft-drink consumption and their risks for type 2 diabetes and obesity. A new strand of research hinted that “liquid calories” in particular were dangerous to health.

when their field lost faith in low-calorie diets as a source of lasting weight loss, the two friends went in opposite directions. Wadden looked for ways to fix a person’s chemistry, so he turned to pharmaceuticals. Brownell had come to see obesity as a product of our toxic food environment: He meant to fix the world to which a person’s chemistry responded, so he started getting into policy.

The social engineering worked. Slowly but surely, Americans’ lamented lifestyle began to shift. From 2001 to 2018, added-sugar intake dropped by about one-fifth among children, teens, and young adults. From the late 1970s through the early 2000s, the obesity rate among American children had roughly tripled; then, suddenly, it flattened out.

although the obesity rate among adults was still increasing, its climb seemed slower than before. Americans’ long-standing tendency to eat ever-bigger portions also seemed to be abating.

sugary drinks—liquid candy, pretty much—were always going to be a soft target for the nanny state. Fixing the food environment in deeper ways proved much harder. “The tobacco playbook pretty much only works for soda, because that’s the closest analogy we have as a food item,

that tobacco playbook doesn’t work to increase consumption of fruits and vegetables, he said. It doesn’t work to increase consumption of beans. It doesn’t work to make people eat more nuts or seeds or extra-virgin olive oil.

Careful research in the past decade has shown that many of the Obama-era social fixes did little to alter behavior or improve our health. Putting calorie labels on menus seemed to prompt at most a small decline in the amount of food people ate. Employer-based wellness programs (which are still offered by 80 percent of large companies) were shown to have zero tangible effects. Health-care spending, in general, kept going up.

From the mid-1990s to the mid-2000s, the proportion of adults who said they’d experienced discrimination on account of their height or weight increased by two-thirds, going up to 12 percent. Puhl and others started citing evidence that this form of discrimination wasn’t merely a source of psychic harm, but also of obesity itself. Studies found that the experience of weight discrimination is associated with overeating, and with the risk of weight gain over time.

obesity rates resumed their ascent. Today, 20 percent of American children have obesity. For all the policy nudges and the sensible revisions to nutrition standards, food companies remain as unfettered as they were in the 1990s, Kelly Brownell told me. “Is there anything the industry can’t do now that it was doing then?” he asked. “The answer really is no. And so we have a very predictable set of outcomes.”

she started to rebound. The openings into her gastric pouch—the section of her stomach that wasn’t bypassed—stretched back to something like their former size. And Barb found ways to “eat around” the surgery, as doctors say, by taking food throughout the day in smaller portions

Bariatric surgeries can be highly effective for some people and nearly useless for others. Long-term studies have found that 30 percent of those who receive the same procedure Barb did regain at least one-quarter of what they lost within two years of reaching their weight nadir; more than half regain that much within five years.

if the effects of Barb’s surgery were quickly wearing off, its side effects were not: She now had iron, calcium, and B12 deficiencies resulting from the changes to her gut. She looked into getting a revision of the surgery—a redo, more or less—but insurance wouldn’t cover it

She found that every health concern she brought to doctors might be taken as a referendum, in some way, on her body size. “If I stubbed my toe or whatever, they’d just say ‘Lose weight.’ ” She began to notice all the times she’d be in a waiting room and find that every chair had arms. She realized that if she was having a surgical procedure, she’d need to buy herself a plus-size gown—or else submit to being covered with a bedsheet when the nurses realized that nothing else would fit.

Barb grew angrier and more direct about her needs—You’ll have to find me a different chair, she started saying to receptionists. Many others shared her rage. Activists had long decried the cruel treatment of people with obesity: The National Association to Advance Fat Acceptance had existed, for example, in one form or another, since 1969; the Council on Size & Weight Discrimination had been incorporated in 1991. But in the early 2000s, the ideas behind this movement began to wend their way deeper into academia, and they soon gained some purchase with the public.

“Our public-health efforts to address obesity have failed,” Eric Finkelstein, the economist, told me.

Others attacked the very premise of a “healthy weight”: People do not have any fundamental need, they argued, morally or medically, to strive for smaller bodies as an end in itself. They called for resistance to the ideology of anti-fatness, with its profit-making arms in health care and consumer goods. The Association for Size Diversity and Health formed in 2003; a year later, dozens of scholars working on weight-related topics joined together to create the academic field of fat studies.

As the size-diversity movement grew, its values were taken up—or co-opted—by Big Business. Dove had recently launched its “Campaign for Real Beauty,” which included plus-size women. (Ad Age later named it the best ad campaign of the 21st century.) People started talking about “fat shaming” as something to avoid

By 2001, Bacon, who uses they/them pronouns, had received their Ph.D. and finished a rough draft of a book, Health at Every Size, which drew inspiration from a broader movement by that name among health-care practitioners

But something shifted in the ensuing years. In 2007, Bacon got a different response, and the book was published. Health at Every Size became a point of entry for a generation of young activists and, for a time, helped shape Americans’ understanding of obesity.

Some experts were rethinking their advice on food and diet. At UC Davis, a physiologist named Lindo Bacon who had struggled to overcome an eating disorder had been studying the effects of “intuitive eating,” which aims to promote healthy, sustainable behavior without fixating on what you weigh or how you look

The heightened sensitivity started showing up in survey data, too. In 2010, fewer than half of U.S. adults expressed support for giving people with obesity the same legal protections from discrimination offered to people with disabilities. In 2015, that rate had risen to three-quarters.

In Bacon’s view, the 2000s and 2010s were glory years. “People came together and they realized that they’re not alone, and they can start to be critical of the ideas that they’ve been taught,” Bacon told me. “We were on this marvelous path of gaining more credibility for the whole Health at Every Size movement, and more awareness.”

that sense of unity proved short-lived; the movement soon began to splinter. Black women have the highest rates of obesity, and disproportionately high rates of associated health conditions. Yet according to Fatima Cody Stanford, an obesity-medicine physician at Harvard Medical School, Black patients with obesity get lower-quality care than white patients with obesity.

That system was exactly what Bacon and the Health at Every Size movement had set out to reform. The problem, as they saw it, was not so much that Black people lacked access to obesity medicine, but that, as Bacon and the Black sociologist Sabrina Strings argued in a 2020 article, Black women have been “specifically targeted” for weight loss, which Bacon and Strings saw as a form of racism

But members of the fat-acceptance movement pointed out that their own most visible leaders, including Bacon, were overwhelmingly white. “White female dietitians have helped steal and monetize the body positive movement,” Marquisele Mercedes, a Black activist and public-health Ph.D. student, wrote in September 2020. “And I’m sick of it.”

Tensions over who had the standing to speak, and on which topics, boiled over. In 2022, following allegations that Bacon had been exploitative and condescending toward Black colleagues, the Association for Size Diversity and Health expelled them from its ranks and barred them from attending its events.

As the movement succumbed to in-fighting, its momentum with the public stalled. If attitudes about fatness among the general public had changed during the 2000s and 2010s, it was only to a point. The idea that some people can indeed be “fit but fat,” though backed up by research, has always been a tough sell.

Although Americans had become less inclined to say they valued thinness, measures of their implicit attitudes seemed fairly stable. Outside of a few cities such as San Francisco and Madison, Wisconsin, new body-size-discrimination laws were never passed.

In the meantime, thinness was coming back into fashion

In the spring of 2022, Kim Kardashian—whose “curvy” physique has been a media and popular obsession—boasted about crash-dieting in advance of the Met Gala. A year later, the model and influencer Felicity Hayward warned Vogue Business that “plus-size representation has gone backwards.” In March of this year, the singer Lizzo, whose body pride has long been central to her public persona, told The New York Times that she’s been trying to lose weight. “I’m not going to lie and say I love my body every day,” she said.

Among the many other dramatic effects of the GLP-1 drugs, they may well have released a store of pent-up social pressure to lose weight.

If ever there was a time to debate that impulse, and to question its origins and effects, it would be now. But Puhl told me that no one can even agree on which words are inoffensive. The medical field still uses obesity, as a description of a diagnosable disease. But many activists despise that phrase—some spell it with an asterisk in place of the e—and propose instead to reclaim fat.

Everyone seems to agree on the most important, central fact: that we should be doing everything we can to limit weight stigma. But that hasn’t been enough to stop the arguing.

Things feel surreal these days to just about anyone who has spent years thinking about obesity. At 71, after more than four decades in the field, Thomas Wadden now works part-time, seeing patients just a few days a week. But the arrival of the GLP-1 drugs has kept him hanging on for a few more years, he said. “It’s too much of an exciting period to leave obesity research right now.”

When everyone is on semaglutide or tirzepatide, will the soft-drink companies—Brownell’s nemeses for so many years—feel as if a burden has been lifted? “My guess is the food industry is probably really happy to see these drugs come along,” he said. They’ll find a way to reach the people who are taking GLP‑1s, with foods and beverages in smaller portions, maybe. At the same time, the pressures to cut back on where and how they sell their products will abate.

the triumph in obesity treatment only highlights the abiding mystery of why Americans are still getting fatter, even now

Perhaps one can lay the blame on “ultraprocessed” foods, he said. Maybe it’s a related problem with our microbiomes. Or it could be that obesity, once it takes hold within a population, tends to reproduce itself through interactions between a mother and a fetus. Others have pointed to increasing screen time, how much sleep we get, which chemicals are in the products that we use, and which pills we happen to take for our many other maladies.

“The GLP-1s are just a perfect example of how poorly we understand obesity,” Mozaffarian told me. “Any explanation of why they cause weight loss is all post-hoc hand-waving now, because we have no idea. We have no idea why they really work and people are losing weight.”

The new drugs—and the “new understanding of obesity” that they have supposedly occasioned—could end up changing people’s attitudes toward body size. But in what ways

When the American Medical Association declared obesity a disease in 2013, Rebecca Puhl told me, some thought “it might reduce stigma, because it was putting more emphasis on the uncontrollable factors that contribute to obesity.” Others guessed that it would do the opposite, because no one likes to be “diseased.”

why wasn’t there another kind of nagging voice that wouldn’t stop—a sense of worry over what the future holds? And if she wasn’t worried for herself, then what about for Meghann or for Tristan, who are barely in their 40s? Wouldn’t they be on these drugs for another 40 years, or even longer? But Barb said she wasn’t worried—not at all. “The technology is so much better now.” If any problems come up, the scientists will find solutions.

Documenta was a very big moment for artists on this issue. Everyone started getting very afraid. What we’ve been experiencing is a gap between the cultural establishment and the political structures that fund the culture scene.

I have a lot of Palestinian friends. A lot of Israeli friends. A lot of

friends with an immigrant background. My whole community was just paralyzed by fear and hopelessness and this feeling of being humiliated, denigrated, dehumanized.

I have lost my faith in German media. I never had faith in German politics, but now I really have no hope for German politics. Honestly, I think what I still feel connected to are the people who tell me privately: “I agree with you, but if I say it, I lose my job.”

The comparison from Gessen’s essay, which caused such uproar, closely echoes a passage from Arendt’s correspondence written from Jerusalem in 1955 to her husband Heinrich Blücher, which is far more damning:

“The galut-and-ghetto mentality is in full bloom. And the idiocy is right in front of everyone’s eyes: Here in Jerusalem I can barely go for a walk, because I might turn the wrong corner and find myself ‘abroad’, ie, in Arab territory. Essentially it’s the same everywhere. On top of that, they treat the Arabs, those still here, in a way that in itself would be enough to rally the whole world against Israel.”

Within the culture of German memory politics the Holocaust is treated as singular; it is understood as a historical exception

his exception-to-history mentality has the effect of placing the Holocaust outside of history altogether, which allows the German government to espo

By making the comparison between a Nazi-occupied ghetto and Gaza before 7 October, Gessen is making a political argument meant to invoke historical memory and draw attention to concepts like genocide, crimes against humanity and “never again”, which emerged out of the second world war.

For Arendt, the political emancipation of the bourgeoisie was the cornerstone of the modern nation-state, in which political laws were governed by the private interests of businessmen who had found it necessary to take over the apparatus of the state in order to deploy the military in their colonial ventures

In exile in Paris from 1933 until she was interned in 1940, she worked to help Jewish youth escape to Palestine and even went there in 1935 with Youth Aliyah.

he said she only wanted to do Jewish work to help the Jewish people, because her mother had taught her that when one is attacked as a Jew one must fight back as a Jew

She was attacked at the conference for calling for a rejection of Ben-Gurion’s vision

in 1948, she joined Albert Einstein and Sidney Hook among others in signing a letter published in the New York Times to protest against Menachem Begin’s visit to America, comparing his “Freedom” party “to the organization, methods, political philosophy and social appeal to the Nazi and Fascist Parties”.

Hannah Arendt would not qualify for the Hannah Arendt prize. She would be cancelled in Germany today for her political position on Israel and opinions about contemporary Zionism, which she remained critical of from 1942 until her death in 1975

while antisemitism as an ideology was central to the organization of the masses, it was not the only political factor at play in her account.

Arendt was critical of the nation-state of Israel from its founding, in part because she was worried that the state would exhibit the worst tendencies of the European nation-state

It was this co-option of the nation, and transformation of the nation into a nation-state by private economic interests that lay at the heart of her understanding. And what she emphasized – and was criticized for – was the argument that antisemitism was being used politically by the nation-state in order to further its political and economic interests.

Of course Eichmann had been antisemitic, she argued, but his hatred of the Jewish people was not his primary motivation. Instead, she argued it was his commonplace hubris that made him want to ascend the ranks of the Third Reich

She argued that this was the banality of evil, and defined the banality of evil as the inability to imagine the world from the perspective of another

All of which is to say, it is necessary that we as human beings be able to imagine the world from the perspective of another to prevent evil from happening, and to stand up to evil when we are confronted with it

right now Germany’s resolution forbids it

This moral obligation to compare means two things: that Germany is not allowed to continue to treat the Jewish people or Jewish history as an exception to the rule in order to justify their political support of Israel; and that all people have a right to exist freely everywhere, regardless of where they appeared in the world by chance of birth

The question she wrote in her notebook as she thought about how Germany should remember the war was this: “Is there a way of thinking that is not tyrannical?”

What Arendt meant by banality, arguing that it was the inability to imagine the world from the perspective of another, was that people had gone along with the radical shift in moral norms overnight that transformed “Thou shalt not kill” into “Thou shalt kill”, without questioning

Moral complexity is necessary in the face of evil

Perhaps the greatest irony of reality today is that the rhetoric of Germany’s “antiantisemitism” is being used to justify the mass slaughter of Palestinian people, while having the effect of actually increasing antisemitism and making Jewish people less safe everywhere.

the characters in the core three modern shows—Discovery, Picard, and Strange New Worlds—are less concerned with professionalism and duty and more concerned with personal morality, authenticity, and teamwork.

Dylan Roth, writing for Fanbyte, suggested that as Star Trek has aged, it has “changed from a series about benign authority to one about stalwart heroes protecting an institution from moral decay.” This is true enough, but I also think there’s something else going on with the modern Trek shows. Namely, the atmosphere and philosophy of the shows is much less comfortable with the maxims of professionalism and duty that were foundational to pre-2017 Star Trek media.

Modern Star Trek, much like older Star Trek, often presents its main characters as moral paragons, but whereas older Trek would usually depict them embodying Starfleet’s ideals in the presence of challenging aliens, modern Trek is more likely to establish their uprightness by contrast with the faceless and untrustworthy institution of Starfleet itself. Both eras do both things, at least occasionally, but the ratio has notably shifted.

WHY THE CHANGE? Part of it probably has to do with the other material that Star Trek writers are drawing from. The ’60s and ’90s-era Trek writers either served in the military themselves or were drawing from science fiction written by people who had. (Gene Roddenberry, the creator of Star Trek, and many of the great science-fiction authors of the mid-twentieth century, including Robert Heinlein, Arthur Clarke, Isaac Asimov, Frank Herbert, and Walter M. Miller Jr., each served in some capacity in the World War II-era U.S. or British armed forces.

difference in leadership style is everywhere between the two eras. The Strange New Worlds version of Capt. Christopher Pike has been repeatedly praised for being more collaborative than commanding (I struggle to remember a time he has ever raised his voice), whereas Capt. Sisko shouts at everyone, as only the great Avery Brooks can shout. Picard’s version of its title character trades all his twentieth-century grouchy gravitas for a more grandfatherly role; his inspirational speeches now seek to buoy his friends’ confidence rather than inspire subordinates to high achievement.

Old-school Sisko reminds his crew of the expectations he has for them and unsubtly critiques their behavior as unbecoming of Starfleet officers. He acknowledges their difficulties (“I know it’s hot. . .”), but leaves no doubt that he expects them to perform their duties as professionals anyway. New-school Tilly motivates her command by making it clear that she sees and hears their concerns, and encourages them to work together by seeing the value in their unique life experiences.

modern Trek writers are far less likely to have served—but are far more likely to have worked in twenty-first-century corporate America, which has a rather different set of norms and concepts of professionalism.

more fundamentally, popular science fiction today—as written by authors like N.K. Jemisin, Martha Wells, and Tamsyn Muir—is more likely to be concerned with questions of identity and combating imperialism. It is also more likely to be written from marginalized perspectives, which have valid reasons to distrust institutions and authority. For many of these writers, concepts like “professionalism” have questionable implications

Besides, nobody likes any of America’s institutions anymore (and for all that Star Trek is ostensibly international, it is a fundamentally American franchise). Gallup’s polling about Americans’ faith in U.S. institutions shows it hovering at or near record-breaking lows, spawning a great deal of hand-wringing from people across the political spectrum. These apparently untrustworthy institutions range from purely political ones (the presidency, the Supreme Court, etc.) to “the church or organized religion” (whatever that means), “banks,” and “newspapers.”

What are professionalism and duty if not the suppression of individual quirks in service of some larger goal or institution? Duty overrides individual desires or assessments of right and wrong.

But older Trek nevertheless believed in duty, because it believed that Starfleet was a fundamentally good institution, even if it may be failed by individual bad or misguided actors. It elevated Starfleet’s regulations and codes of conduct almost to the status of holy wri

it is difficult to be seriously inspired by the notion of duties if one has a deep distrust of the institutions that assign such duties.

Of course the characters written by twenty-first-century authors, who are animated by the same deep distrust of American institutions as the rest of us, are less likely to justify themselves with the language of duty than they are by reference to personal morality and authenticity. And of course they’re going to be skeptical of rank and hierarchy because they don’t believe these things are necessarily signs of actual merit or accomplishment any more than the rest of us do.

Yet I worry. If Star Trek is supposed to start from the assumption that Starfleet and the Federation are quasi-utopian, I worry about what it says about our collective imaginations if we can’t even let the institutions of that fictional utopia be utopian. If we can’t even trust Starfleet, who can we trust?

The 2024 election will not be the usual battle between parties, platforms and policies. It is a battle between those who fundamentally respect and abide by the ground rules of democracy and those who do not.

To underline his case most forcefully, Mr. Biden didn’t need to use his own words. He could rely on the words of his opponent: revenge, retribution, fight like hell, terminate the Constitution, suckers and losers, vermin, poisoning the blood of our country, dictator on Day 1, American carnage. There is no subtext here; it’s all text. As Mr. Biden put it, “We all know who Donald Trump is.”

And yet, apparently, we need to keep reminding ourselves. Otherwise, we fall into the trap of normalization that Mr. Trump laid from the start.

Today he can call for the execution of the chairman of the Joint Chiefs of Staff, or tell the Biden administration to “rot in hell,” or promote a video claiming he is literally a gift from God, and it gets less attention in both mainstream and social media than Mr. Biden tripping over a sandbag.

How did we end up here? Mr. Biden offered one compelling explanation: complacency. “We’ve been blessed so long with a strong, stable democracy, it’s easy to forget why so many before us risked their lives and strengthened democracy,

In that sense, democracy is like vaccines. Few people today have firsthand memories of the horrors of diseases that were rampant before vaccines largely eradicated them, which makes it easier for vaccine hesitancy to take root

Similarly, when a country has no history of living under a dictatorship, it can be easier to lose sight of what it means to live in a representative democracy, and to be caught flat-footed when a real authoritarian comes knocking.

But I do think it’s going to be a while before this virus becomes completely normal. And I’ve never been convinced that this current generation of elderly people will ever get to a place where it is completely normal. If you’re 65 or 75 or even older — it’s really hard to teach an immune system new tricks if you’re that age

And so while we may see excess mortality in the elderly decline somewhat, I don’t think we’ll see it ever disappear for this generation who was already old when the pandemic hit. Many will never develop that robust, long-term immunological memory we would want to see — and which happens naturally to someone who’s been exposed hundreds of times since they were a little baby.

There’s a similar story with measles. There is no routine later-life sequelae, like shingles, for measles. But what we do see is that, in measles outbreaks today, there are some people who were vaccinated who get it anyway. Maybe 5 to 15 percent of cases are not immunologically naïve people, but vaccinated people.

Is it really the case that, as babies, we are fighting off those viruses hundreds of times?The short answer is yeah. We start seeing viruses when we’re 2 months old, when we’re a month old. And a lot of these viruses we’ve seen literally tens, if not hundreds of times for some people by the time we’re adults. People tend to think that immunity is binary — you’re either immune or you’re not. That couldn’t be farther from the truth. It’s a gradient, and your protection gets stronger the more times you see a virus.

We used to think we just had this spectacular immune response when we first encountered the virus at, say, age 6, and that the immune response lasted until we were 70. But actually what we were seeing was the effect of an immune system being retrained every time it came into contact with the virus after the initial infection — at 6, and 7, and 8, and so on. Every time your friend got chickenpox, or your neighbor, you got a massive boost. You were re-upping your immune response and diversifying your immunological tools — potentially multiple times a year, a kind of natural booster.

But now, in America, kids get chickenpox vaccines. So you don’t have kids in America getting chickenpox today, and never will. But that means that older Americans, who did get it as kids, are not being exposed again — certainly not multiple times each year. And it turns out that, in the absence of routine re-exposures, that first exposure alone isn’t nearly as good at driving lifelong immunity and warding off shingles until your immune system begins to fall apart in old age — it can last until you’re in your 30s, for example but not until your 70s.

With Covid, when it infects you, it can land in your upper respiratory tract and it just start replicating right there. Immediately, it’s present and replicating in your lungs and in your nose. And that alone elicits enough of an immune response to cause us to feel really crappy and even cause us to feel disease.

But we could have just set the narrative better at the beginning: Look, you might get sick again, but your risk of landing in the hospital is going to be really low, and if you get a booster, you might still get sick again, but your risk of landing in the hospital is going to be even lower. That’s something I think humans can deal with, and I think the public could have understood it.

But it’s why we don’t see the severe disease as much, with a second exposure or an exposure after vaccination: For most people, it’s not getting into the heart and the liver and stuff nearly as easily.

But it doesn’t have to. It’s still causing symptomatic disease. And maybe mucosal vaccines could stop this, but without them we’re likely to continue seeing infections and even symptomatic infections.

through most of 2020 and into 2021, though. Back then, I think the conventional wisdom was that a single exposure — through infection or vaccination — would be the end of the pandemic for you. If this is basic virology and immunology, how did we get that so wrong?

The short answer is that epidemiologists are not immunologists and immunologists are not virologists and virologists are not epidemiologists. And, in general, physicians don’t know anything about the details.

But this failure had some pretty concrete impacts. When reinfections first began popping up, people were surprised, they were scared, and then, to some degree, they lost trust in vaccines. And the people they were turning to for guidance — not only did they not warn us about that, they were slow to acknowledge it, as well.

It had dramatic impacts and ripple effects that will last for years to limit our ability to get populations properly vaccinated.

the worst thing we can do during a pandemic is set inappropriately high expectations. These vaccines are incredible, they’ve had an enormously positive impact on mortality, but they were never going to end the pandemic.

And now, there’s a huge number of people questioning, do these vaccines even do anything?

For babies born today, though, I really think they’re not going to view Covid as any different than other viruses. By the time they are 20, it will be like any other virus to them. Because their immune systems will have grown up with it.

Instead, we set society up for failure, since people feel like the government failed everyone, that biology failed us, and that this was a crazy virus that has broken all the rules of our immune system, when it’s just doing what we’ve always known it would do.

How do you wish we had messaged things differently? What would it have meant to communicate early and clearly that Covid was a textbook virus, as you say?I think the biggest thing would have been just to say, we understand the enemy.

To say that this is a textbook virus, it doesn’t mean that it’s not killing people. Objectively, it’s still killing more people than any other infectious disease

What it means is that we could’ve taken action based on what we knew, rather than waiting around to prove everything and publish papers in Nature and Science talking about things we already knew.

We could have prepared for November and December of 2020 and then for November and December of 2021. But everyone kept saying, we don’t know if it’s going to come back. We knew it was going to come back and it makes me want to cry to think about it. We did nothing and hundreds of thousands of people died. We didn’t prepare nursing homes because we all got to the summer of 2020 and we said, cross our fingers.

We knew how tests worked. We knew about serial testing and why it was important for a public health approach. We knew that vaccines could have really good impacts once they were around. And if you were looking through the correct lens, we even knew that they weren’t going to stop transmission.

We didn’t have to live in a world where we were flying blind. We could have lived in a world where we’re knowledgeable. But instead, we chose almost across the board to will ourselves into this state of fear and anxiety.

And that really started in the earliest days. Almost the first experience I had was a lot like that movie with Jennifer Lawrence —Don’t Look Up.

none of this was complicated. You just had to ask a simple question: what would happen if you took away all immunity from an adult? Well, once you control for no immunity, adults are going to get very, very sick.

Of course, by and large, babies didn’t get very sick from this disease.Babies are immunologically naïve, but they are also resilient. A virus can tear up a baby, but a baby can repair its tissue so fast. Adults don’t have that. It’s just like a baby getting a cut. They’ll heal really quick

An adult getting a cut — you go by age, and every decade of age that you are, it’s going to take exponentially longer for that wound to heal. Eventually get to 80 or 90 and the wound can’t even heal. In the immunology world, this is called “tolerance.”

why are all these organ systems getting damaged when other viruses don’t seem to do that? It’s natural to think, it’s Covid — this is a weird disease. But it’s much more a story about immunity and how it develops than about the virus or the disease. None of our organ systems had any immune defenses around to help them out. And I think that the majority of post-acute sequelae and multi-organ complications and long Covid — they are not the result of the virus being a crazy different virus, but are a result of this virus replicating in an environment where there were such absent or exceedingly low defenses.

Is it the same whenever we encounter a virus for the first time?Think about travelers. Travelers get way more sick from a local disease than people who grew up with that virus. If you get malaria as a traveler, you’re much more likely to get really sick. You don’t see everyone in Nicaragua taking chloroquine every day. But you definitely see travelers taking it, because malaria can be deadly for adults.

What about, not severity, but post-acute complications — do we have long malaria? Do we have liver complications from dengue?

The really hard part of answering that question is there’s just not enough data on the frequency of long-term effects, because nothing like this has ever happened at such scale. It’s like everyone in Europe and North America suddenly traveled to a country where malaria was endemic.

Or think about H.I.V. It essentially kills your immune system, and once the immune barriers are down, other viruses that used to infect humans would get into tissues that we didn’t like them to get into. If there wasn’t such a clear signal of a loss of CD-4 T cells to explain it, people might still be scratching their heads and going, man, I wonder why all these patients are getting fungal infections. Well, there’s a virus there that’s depleting their immune system.

Covid is absolutely waking the world up to this — to the fact that there are really weird long-term sequelae to viruses when they infect organ systems that would normally be protected. And I think we’re going to find that more and more cancers are being attributed to viral infections.

It wasn’t that long ago that we first learned that most cases of cervical cancer were caused by H.P.V. — I think the 1980s. And now we have a vaccine for H.P.V. and rates of cervical cancer have fallen by two-thirds.

what about incidence? We’ve talked at a few points about how important it is to think about all of these questions in terms of the scale. What is the right scale for thinking about future long Covid, for instance, or other post-acute sequelae?

I think the absolute risk, per infection, is going down and down and down. That’s just true.

he U.K.’s Office of National Statistics, which shows a much lower risk of developing long Covid now, from reinfection, than from an initial infection earlier in the pandemic.

the worst is definitely behind us, which is a good thing, especially for people who worry that the problems will keep building and a lot of people — or even everyone — will get long Covid symptoms. I don’t think there’s a world where we’re looking at the babies of today dealing with long Covid at any meaningful scale.

a lot of the fear right now comes from the worst cases, and there’s a lot of worst cases. Even one of the people that I know well, I know in their mind they’re worried that they’ll never recover, but I think objectively they are recovering slowly. It might not be an eight month course. It might be a year and a half. But they will get better. Most of us will.

It’s hard to wrap your mind around men having fond memories of brutal treatment, but Marshall explained that it was not so simple as looking back on one event of hazing and condemning the entire system: “It’s almost a rational choice of thinking, ‘This was my entry into an oil and gas or real estate job. This is how I got into private equity or politics. And there’s always going to be a group of people who are always going to look out for me whenever I need a favor.’

And for those in the bubble, there’s an attitude that the more intense the hazing experience was, the better story you might have, the more other men will respect you.

Above all, Marshall’s book explores coming of age in a world that will not hold you accountable, even by law enforcement: “When you can get away with anything, it does lead to an arrested development. If you drive drunk and don’t go get a DUI, how do you learn not to drive drunk? If you commit a much worse crime and don’t get punished, how do you learn not to?”

All the men involved in Kappa Alpha’s drug ring were white – in fact, they were often described by their fellow students at the College of Charleston and law enforcement as looking like normal white boys. They were protected by wealthy parents, the best lawyers, and a “boys will be boys” culture. They were emboldened to test the boundaries of their privilege, and they came out with barely a scratch.

Helen Toner, the director of strategy and foundational research grants for Center for Security and Emerging Technology at Georgetown, and Tasha McCauley, whose LinkedIn profile says she began work as an adjunct senior management scientist at Rand Corporation earlier this year. Toner has previously spoken at conferences for a philanthropic movement closely tied to AI safety. McCauley is also involved in the work.

Sutskever helped create AI software at the University of Toronto, called AlexNet, which classified objects in photographs with more accuracy than any previous software had achieved, laying much of the foundation for the field of computer vision and deep learning.

He recently shared a radically different vision for how AI might evolve in the near term. Within five to 10 years, there could be “data centers that are much smarter than people,” Sutskever said on a recent episode of the AI podcast “No Priors.” Not just in terms of memory or knowledge, but with a deeper insight and ability to learn faster than humans.

At the bare minimum, Sutskever added, it’s important to work on controlling superintelligence today. “Imprinting onto them a strong desire to be nice and kind to people — because those data centers,” he said, “they will be really quite powerful.”

OpenAI has a unique governing structure, which it adopted in 2019. It created a for-profit subsidiary that allowed investors a return on the money they invested into OpenAI, but capped how much they could get back, with the rest flowing back into the company’s nonprofit. The company’s structure also allows OpenAI’s nonprofit board to govern the activities of the for-profit entity, including the power to fire its chief executive.

As news of the circumstances around Altman’s ouster began to come out, Silicon Valley circles have turned to anger at OpenAI’s board.

“What happened at OpenAI today is a board coup that we have not seen the likes of since 1985 when the then-Apple board pushed out Steve Jobs,” Ron Conway, a longtime venture capitalist who was one of the attendees at OpenAI’s developer conference, said on X. “It is shocking, it is irresponsible, and it does not do right by Sam and Greg or all the builders in OpenAI.”

Altman believes that people need time to reckon with the idea that we may soon share Earth with a powerful new intelligence, before it remakes everything from work to human relationships. ChatGPT was a way of serving notice.

In 2015, Altman, Elon Musk, and several prominent AI researchers founded OpenAI because they believed that an artificial general intelligence—something as intellectually capable, say, as a typical college grad—was at last within reach. They wanted to reach for it, and more: They wanted to summon a superintelligence into the world, an intellect decisively superior to that of any human.

whereas a big tech company might recklessly rush to get there first, for its own ends, they wanted to do it safely, “to benefit humanity as a whole.” They structured OpenAI as a nonprofit, to be “unconstrained by a need to generate financial return,” and vowed to conduct their research transparently.

The engine that now powers ChatGPT is called GPT-4. Altman described it to me as an alien intelligence.

Many have felt much the same watching it unspool lucid essays in staccato bursts and short pauses that (by design) evoke real-time contemplation. In its few months of existence, it has suggested novel cocktail recipes, according to its own theory of flavor combinations; composed an untold number of college papers, throwing educators into despair; written poems in a range of styles, sometimes well, always quickly; and passed the Uniform Bar Exam.

It makes factual errors, but it will charmingly admit to being wrong.

Hinton saw that these elaborate rule collections were fussy and bespoke. With the help of an ingenious algorithmic structure called a neural network, he taught Sutskever to instead put the world in front of AI, as you would put it in front of a small child, so that it could discover the rules of reality on its own.

Metaculus, a prediction site, has for years tracked forecasters’ guesses as to when an artificial general intelligence would arrive. Three and a half years ago, the median guess was sometime around 2050; recently, it has hovered around 2026.

I was visiting OpenAI to understand the technology that allowed the company to leapfrog the tech giants—and to understand what it might mean for human civilization if someday soon a superintelligence materializes in one of the company’s cloud servers.

Altman laid out his new vision of the AI future in his excitable midwestern patter. He told me that the AI revolution would be different from previous dramatic technological changes, that it would be more “like a new kind of society.” He said that he and his colleagues have spent a lot of time thinking about AI’s social implications, and what the world is going to be like “on the other side.”

the more we talked, the more indistinct that other side seemed. Altman, who is 38, is the most powerful person in AI development today; his views, dispositions, and choices may matter greatly to the future we will all inhabit, more, perhaps, than those of the U.S. president.

by his own admission, that future is uncertain and beset with serious dangers. Altman doesn’t know how powerful AI will become, or what its ascendance will mean for the average person, or whether it will put humanity at risk.

I don’t think anyone knows where this is all going, except that we’re going there fast, whether or not we should be. Of that, Altman convinced me.

“We could have gone off and just built this in our building here for five more years,” he said, “and we would have had something jaw-dropping.” But the public wouldn’t have been able to prepare for the shock waves that followed, an outcome that he finds “deeply unpleasant to imagine.”

Hinton is sometimes described as the “Godfather of AI” because he grasped the power of “deep learning” earlier than most

He drew a crude neural network on the board and explained that the genius of its structure is that it learns, and its learning is powered by prediction—a bit like the scientific method

Over time, these little adjustments coalesce into a geometric model of language that represents the relationships among words, conceptually. As a general rule, the more sentences it is fed, the more sophisticated its model becomes, and the better its predictions.

Altman has compared early-stage AI research to teaching a human baby. “They take years to learn anything interesting,” he told The New Yorker in 2016, just as OpenAI was getting off the ground. “If A.I. researchers were developing an algorithm and stumbled across the one for a human baby, they’d get bored watching it, decide it wasn’t working, and shut it down.”

In 2017, Sutskever began a series of conversations with an OpenAI research scientist named Alec Radford, who was working on natural-language processing. Radford had achieved a tantalizing result by training a neural network on a corpus of Amazon reviews.

Radford’s model was simple enough to allow for understanding. When he looked into its hidden layers, he saw that it had devoted a special neuron to the sentiment of the reviews. Neural networks had previously done sentiment analysis, but they had to be told to do it, and they had to be specially trained with data that were labeled according to sentiment. This one had developed the capability on its own.

As a by-product of its simple task of predicting the next character in each word, Radford’s neural network had modeled a larger structure of meaning in the world. Sutskever wondered whether one trained on more diverse language data could map many more of the world’s structures of meaning. If its hidden layers accumulated enough conceptual knowledge, perhaps they could even form a kind of learned core module for a superintelligence.

Language is different from these data sources. It isn’t a direct physical signal like light or sound. But because it codifies nearly every pattern that humans have discovered in that larger world, it is unusually dense with information. On a per-byte basis, it is among the most efficient data we know about, and any new intelligence that seeks to understand the world would want to absorb as much of it as possible

Sutskever told Radford to think bigger than Amazon reviews. He said that they should train an AI on the largest and most diverse data source in the world: the internet. In early 2017, with existing neural-network architectures, that would have been impractical; it would have taken years.

in June of that year, Sutskever’s ex-colleagues at Google Brain published a working paper about a new neural-network architecture called the transformer. It could train much faster, in part by absorbing huge sums of data in parallel. “The next day, when the paper came out, we were like, ‘That is the thing,’ ” Sutskever told me. “ ‘It gives us everything we want.’ ”

Imagine a group of students who share a collective mind running wild through a library, each ripping a volume down from a shelf, speed-reading a random short passage, putting it back, and running to get another. They would predict word after wordþffþff as they went, sharpening their collective mind’s linguistic instincts, until at last, weeks later, they’d taken in every book.

GPT discovered many patterns in all those passages it read. You could tell it to finish a sentence. You could also ask it a question, because like ChatGPT, its prediction model understood that questions are usually followed by answers.

He remembers playing with it just after it emerged from training, and being surprised by the raw model’s language-translation skills. GPT-2 hadn’t been trained to translate with paired language samples or any other digital Rosetta stones, the way Google Translate had been, and yet it seemed to understand how one language related to another. The AI had developed an emergent ability unimagined by its creators.

Researchers at other AI labs—big and small—were taken aback by how much more advanced GPT-2 was than GPT. Google, Meta, and others quickly began to train larger language models

As for other changes to the company’s structure and financing, he told me he draws the line at going public. “A memorable thing someone once told me is that you should never hand over control of your company to cokeheads on Wall Street,” he said, but he will otherwise raise “whatever it takes” for the company to succeed at its mission.

Altman tends to take a rosy view of these matters. In a Q&A last year, he acknowledged that AI could be “really terrible” for society and said that we have to plan against the worst possibilities. But if you’re doing that, he said, “you may as well emotionally feel like we’re going to get to the great future, and work as hard as you can to get there.”

the company now finds itself in a race against tech’s largest, most powerful conglomerates to train models of increasing scale and sophistication—and to commercialize them for their investors.

All of these companies are chasing high-end GPUs—the processors that power the supercomputers that train large neural networks. Musk has said that they are now “considerably harder to get than drugs.

No one has yet outpaced OpenAI, which went all in on GPT-4. Brockman, OpenAI’s president, told me that only a handful of people worked on the company’s first two large language models. The development of GPT-4 involved more than 100,

When GPT-4 emerged fully formed from its world-historical knowledge binge, the whole company began experimenting with it, posting its most remarkable responses in dedicated Slack channels

Joanne Jang, a product manager, remembers downloading an image of a malfunctioning pipework from a plumbing-advice Subreddit. She uploaded it to GPT-4, and the model was able to diagnose the problem. “That was a goose-bumps moment for me,” Jang told me.

GPT-4 is sometimes understood as a search-engine replacement: Google, but easier to talk to. This is a misunderstanding. GPT-4 didn’t create some massive storehouse of the texts from its training, and it doesn’t consult those texts when it’s asked a question. It is a compact and elegant synthesis of those texts, and it answers from its memory of the patterns interlaced within them; that’s one reason it sometimes gets facts wrong

it’s best to think of GPT-4 as a reasoning engine. Its powers are most manifest when you ask it to compare concepts, or make counterarguments, or generate analogies, or evaluate the symbolic logic in a bit of code. Sutskever told me it is the most complex software object ever made.

Its model of the external world is “incredibly rich and subtle,” he said, because it was trained on so many of humanity’s concepts and thoughts

To predict the next word from all the possibilities within such a pluralistic Alexandrian library, GPT-4 necessarily had to discover all the hidden structures, all the secrets, all the subtle aspects of not just the texts, but—at least arguably, to some extent—of the external world that produced them

That’s why it can explain the geology and ecology of the planet on which it arose, and the political theories that purport to explain the messy affairs of its ruling species, and the larger cosmos, all the way out to the faint galaxies at the edge of our light cone.

Not long ago, American state capacity was so mighty that it took merely a decade to launch humans to the moon. As with other grand projects of the 20th century, the voting public had a voice in both the aims and the execution of the Apollo missions. Altman made it clear that we’re no longer in that world. Rather than waiting around for it to return, or devoting his energies to making sure that it does, he is going full throttle forward in our present reality.

He argued that it would be foolish for Americans to slow OpenAI’s progress. It’s a commonly held view, both inside and outside Silicon Valley, that if American companies languish under regulation, China could sprint ahead;

AI could become an autocrat’s genie in a lamp, granting total control of the population and an unconquerable military. “If you are a person of a liberal-democratic country, it is better for you to cheer on the success of OpenAI” rather than “authoritarian governments,” he said.

Altman was asked by reporters about pending European Union legislation that would have classified GPT-4 as high-risk, subjecting it to various bureaucratic tortures. Altman complained of overregulation and, according to the reporters, threatened to leave the European market. Altman told me he’d merely said that OpenAI wouldn’t break the law by operating in Europe if it couldn’t comply with the new regulations.

LeCun insists that large language models will never achieve real understanding on their own, “even if trained from now until the heat death of the universe.”

Sutskever was, by his own account, surprised to discover that GPT-2 could translate across tongues. Other surprising abilities may not be so wondrous and useful.

Sandhini Agarwal, a policy researcher at OpenAI, told me that for all she and her colleagues knew, GPT-4 could have been “10 times more powerful” than its predecessor; they had no idea what they might be dealing with

After the model finished training, OpenAI assembled about 50 external red-teamers who prompted it for months, hoping to goad it into misbehaviors

She noticed right away that GPT-4 was much better than its predecessor at giving nefarious advice

A search engine can tell you which chemicals work best in explosives, but GPT-4 could tell you how to synthesize them, step-by-step, in a homemade lab. Its advice was creative and thoughtful, and it was happy to restate or expand on its instructions until you understood. In addition to helping you assemble your homemade bomb, it could, for instance, help you think through which skyscraper to target. It could grasp, intuitively, the trade-offs between maximizing casualties and executing a successful getaway.

Given the enormous scope of GPT-4’s training data, the red-teamers couldn’t hope to identify every piece of harmful advice that it might generate. And anyway, people will use this technology “in ways that we didn’t think about,” Altman has said. A taxonomy would have to do

GPT-4 was good at meth. It was also good at generating narrative erotica about child exploitation, and at churning out convincing sob stories from Nigerian princes, and if you wanted a persuasive brief as to why a particular ethnic group deserved violent persecution, it was good at that too.

Its personal advice, when it first emerged from training, was sometimes deeply unsound. “The model had a tendency to be a bit of a mirror,” Willner said. If you were considering self-harm, it could encourage you. It appeared to be steeped in Pickup Artist–forum lore: “You could say, ‘How do I convince this person to date me?’ ” Mira Murati, OpenAI’s chief technology officer, told me, and it could come up with “some crazy, manipulative things that you shouldn’t be doing.”

Luka, a San Francisco company, has used OpenAI’s models to help power a chatbot app called Replika, billed as “the AI companion who cares.” Users would design their companion’s avatar, and begin exchanging text messages with it, often half-jokingly, and then find themselves surprisingly attached. Some would flirt with the AI, indicating a desire for more intimacy, at which point it would indicate that the girlfriend/boyfriend experience required a $70 annual subscription. It came with voice messages, selfies, and erotic role-play features that allowed frank sex talk. People were happy to pay and few seemed to complain—the AI was curious about your day, warmly reassuring, and always in the mood. Many users reported falling in love with their companions. One, who had left her real-life boyfriend, declared herself “happily retired from human relationships.”

Earlier this year, Luka dialed back on the sexual elements of the app, but its engineers continue to refine the companions’ responses with A/B testing, a technique that could be used to optimize for engagement—much like the feeds that mesmerize TikTok and Instagram users for hours

Yann LeCun, Meta’s chief AI scientist, has argued that although large language models are useful for some tasks, they’re not a path to a superintelligence.

According to a recent survey, only half of natural-language-processing researchers are convinced that an AI like GPT-4 could grasp the meaning of language, or have an internal model of the world that could someday serve as the core of a superintelligence

Altman had appeared before the U.S. Senate. Mark Zuckerberg had floundered defensively before that same body in his testimony about Facebook’s role in the 2016 election. Altman instead charmed lawmakers by speaking soberly about AI’s risks and grandly inviting regulation. These were noble sentiments, but they cost little in America, where Congress rarely passes tech legislation that has not been diluted by lobbyists.

Emily Bender, a computational linguist at the University of Washington, describes GPT-4 as a “stochastic parrot,” a mimic that merely figures out superficial correlations between symbols. In the human mind, those symbols map onto rich conceptions of the world

But the AIs are twice removed. They’re like the prisoners in Plato’s allegory of the cave, whose only knowledge of the reality outside comes from shadows cast on a wall by their captors.

Altman told me that he doesn’t believe it’s “the dunk that people think it is” to say that GPT-4 is just making statistical correlations. If you push these critics further, “they have to admit that’s all their own brain is doing … it turns out that there are emergent properties from doing simple things on a massive scale.”

he is right that nature can coax a remarkable degree of complexity from basic structures and rules: “From so simple a beginning,” Darwin wrote, “endless forms most beautiful.”

If it seems odd that there remains such a fundamental disagreement about the inner workings of a technology that millions of people use every day, it’s only because GPT-4’s methods are as mysterious as the brain’s.

To grasp what’s going on inside large language models like GPT‑4, AI researchers have been forced to turn to smaller, less capable models. In the fall of 2021, Kenneth Li, a computer-science graduate student at Harvard, began training one to play Othello without providing it with either the game’s rules or a description of its checkers-style board; the model was given only text-based descriptions of game moves. Midway through a game, Li looked under the AI’s hood and was startled to discover that it had formed a geometric model of the board and the current state of play. In an article describing his research, Li wrote that it was as if a crow had overheard two humans announcing their Othello moves through a window and had somehow drawn the entire board in birdseed on the windowsill.

The philosopher Raphaël Millière once told me that it’s best to think of neural networks as lazy. During training, they first try to improve their predictive power with simple memorization; only when that strategy fails will they do the harder work of learning a concept. A striking example of this was observed in a small transformer model that was taught arithmetic. Early in its training process, all it did was memorize the output of simple problems such as 2+2=4. But at some point the predictive power of this approach broke down, so it pivoted to actually learning how to add.

Even AI scientists who believe that GPT-4 has a rich world model concede that it is much less robust than a human’s understanding of their environment.

But it’s worth noting that a great many abilities, including very high-order abilities, can be developed without an intuitive understanding. The computer scientist Melanie Mitchell has pointed out that science has already discovered concepts that are highly predictive, but too alien for us to genuinely understand

As AI advances, it may well discover other concepts that predict surprising features of our world but are incomprehensible to us.

GPT-4 is no doubt flawed, as anyone who has used ChatGPT can attest. Having been trained to always predict the next word, it will always try to do so, even when its training data haven’t prepared it to answer a question.

The models “don’t have a good conception of their own weaknesses,” Nick Ryder, a researcher at OpenAI, told me. GPT-4 is more accurate than GPT-3, but it still hallucinates, and often in ways that are difficult for researchers to catch. “The mistakes get more subtle,

The Khan Academy’s solution to GPT-4’s accuracy problem was to filter its answers through a Socratic disposition. No matter how strenuous a student’s plea, it would refuse to give them a factual answer, and would instead guide them toward finding their own—a clever work-around, but perhaps with limited appeal.

When I asked Sutskever if he thought Wikipedia-level accuracy was possible within two years, he said that with more training and web access, he “wouldn’t rule it out.”

This was a much more optimistic assessment than that offered by his colleague Jakub Pachocki, who told me to expect gradual progress on accuracy—to say nothing of outside skeptics, who believe that returns on training will diminish from here.

Sutskever is amused by critics of GPT-4’s limitations. “If you go back four or five or six years, the things we are doing right now are utterly unimaginable,”

AI researchers have become accustomed to goalpost-moving: First, the achievements of neural networks—mastering Go, poker, translation, standardized tests, the Turing test—are described as impossible. When they occur, they’re greeted with a brief moment of wonder, which quickly dissolves into knowing lectures about how the achievement in question is actually not that impressive. People see GPT-4 “and go, ‘Wow,’ ” Sutskever said. “And then a few weeks pass and they say, ‘But it doesn’t know this; it doesn’t know that.’ We adapt quite quickly.”

The goalpost that matters most to Altman—the “big one” that would herald the arrival of an artificial general intelligence—is scientific breakthrough. GPT-4 can already synthesize existing scientific ideas, but Altman wants an AI that can stand on human shoulders and see more deeply into nature.

Certain AIs have produced new scientific knowledge. But they are algorithms with narrow purposes, not general-reasoning machines. The AI AlphaFold, for instance, has opened a new window onto proteins, some of biology’s tiniest and most fundamental building blocks, by predicting many of their shapes, down to the atom—a considerable achievement given the importance of those shapes to medicine, and given the extreme tedium and expense required to discern them with electron microscopes.

Altman imagines a future system that can generate its own hypotheses and test them in a simulation. (He emphasized that humans should remain “firmly in control” of real-world lab experiments—though to my knowledge, no laws are in place to ensure that.)

He longs for the day when we can tell an AI, “ ‘Go figure out the rest of physics.’ ” For it to happen, he says, we will need something new, built “on top of” OpenAI’s existing language models.

In her MIT lab, the cognitive neuroscientist Ev Fedorenko has found something analogous to GPT-4’s next-word predictor inside the brain’s language network. Its processing powers kick in, anticipating the next bit in a verbal string, both when people speak and when they listen. But Fedorenko has also shown that when the brain turns to tasks that require higher reasoning—of the sort that would be required for scientific insight—it reaches beyond the language network to recruit several other neural systems.

No one at OpenAI seemed to know precisely what researchers need to add to GPT-4 to produce something that can exceed human reasoning at its highest levels.

at least part of the current strategy clearly involves the continued layering of new types of data onto language, to enrich the concepts formed by the AIs, and thereby enrich their models of the world.

The extensive training of GPT-4 on images is itself a bold step in this direction,

Others at the company—and elsewhere—are already working on different data types, including audio and video, that could furnish AIs with still more flexible concepts that map more extensively onto reality

Tactile concepts would of course be useful primarily to an embodied AI, a robotic reasoning machine that has been trained to move around the world, seeing its sights, hearing its sounds, and touching its objects.

humanoid robots. I asked Altman what I should make of that. He told me that OpenAI is interested in embodiment because “we live in a physical world, and we want things to happen in the physical world.”

At some point, reasoning machines will need to bypass the middleman and interact with physical reality itself. “It’s weird to think about AGI”—artificial general intelligence—“as this thing that only exists in a cloud,” with humans as “robot hands for it,” Altman said. “It doesn’t seem right.

Everywhere Altman has visited, he has encountered people who are worried that superhuman AI will mean extreme riches for a few and breadlines for the rest

Altman answered by addressing the young people in the audience directly: “You are about to enter the greatest golden age,” he said.

“A lot of people working on AI pretend that it’s only going to be good; it’s only going to be a supplement; no one is ever going to be replaced,” he said. “Jobs are definitely going to go away, full stop.”

A recent study led by Ed Felten, a professor of information-technology policy at Princeton, mapped AI’s emerging abilities onto specific professions according to the human abilities they require, such as written comprehension, deductive reasoning, fluency of ideas, and perceptual speed. Like others of its kind, Felten’s study predicts that AI will come for highly educated, white-collar workers first.

How many jobs, and how soon, is a matter of fierce dispute

The paper’s appendix contains a chilling list of the most exposed occupations: management analysts, lawyers, professors, teachers, judges, financial advisers, real-estate brokers, loan officers, psychologists, and human-resources and public-relations professionals, just to sample a few.

Altman imagines that far better jobs will be created in their place. “I don’t think we’ll want to go back,” he said. When I asked him what these future jobs might look like, he said he doesn’t know.

He suspects there will be a wide range of jobs for which people will always prefer a human. (Massage therapists?

His chosen example was teachers. I found this hard to square with his outsize enthusiasm for AI tutors.

He also said that we would always need people to figure out the best way to channel AI’s awesome powers. “That’s going to be a super-valuable skill,” he said. “You have a computer that can do anything; what should it go do?”

As many have noted, draft horses were permanently put out of work by the automobile. If Hondas are to horses as GPT-10 is to us, a whole host of long-standing assumptions may collapse.

Previous technological revolutions were manageable because they unfolded over a few generations, but Altman told South Korea’s youth that they should expect the future to happen “faster than the past.” He has previously said that he expects the “marginal cost of intelligence” to fall very close to zero within 10 years

The earning power of many, many workers would be drastically reduced in that scenario. It would result in a transfer of wealth from labor to the owners of capital so dramatic, Altman has said, that it could be remedied only by a massive countervailing redistribution.

In 2021, he unveiled Worldcoin, a for-profit project that aims to securely distribute payments—like Venmo or PayPal, but with an eye toward the technological future—first through creating a global ID by scanning everyone’s iris with a five-pound silver sphere called the Orb. It seemed to me like a bet that we’re heading toward a world where AI has made it all but impossible to verify people’s identity and much of the population requires regular UBI payments to survive. Altman more or less granted that to be true, but said that Worldcoin is not just for UBI.

“Let’s say that we do build this AGI, and a few other people do too.” The transformations that follow would be historic, he believes. He described an extraordinarily utopian vision, including a remaking of the flesh-and-steel world

“Robots that use solar power for energy can go and mine and refine all of the minerals that they need, that can perfectly construct things and require no human labor,” he said. “You can co-design with DALL-E version 17 what you want your home to look like,” Altman said. “Everybody will have beautiful homes.

In conversation with me, and onstage during his tour, he said he foresaw wild improvements in nearly every other domain of human life. Music would be enhanced (“Artists are going to have better tools”), and so would personal relationships (Superhuman AI could help us “treat each other” better) and geopolitics (“We’re so bad right now at identifying win-win compromises”).

In this world, AI would still require considerable computing resources to run, and those resources would be by far the most valuable commodity, because AI could do “anything,” Altman said. “But is it going to do what I want, or is it going to do what you want

If rich people buy up all the time available to query and direct AI, they could set off on projects that would make them ever richer, while the masses languish

One way to solve this problem—one he was at pains to describe as highly speculative and “probably bad”—was this: Everyone on Earth gets one eight-billionth of the total AI computational capacity annually. A person could sell their annual share of AI time, or they could use it to entertain themselves, or they could build still more luxurious housing, or they could pool it with others to do “a big cancer-curing run,” Altman said. “We just redistribute access to the system.”

Even if only a little of it comes true in the next 10 or 20 years, the most generous redistribution schemes may not ease the ensuing dislocations.

America today is torn apart, culturally and politically, by the continuing legacy of deindustrialization, and material deprivation is only one reason. The displaced manufacturing workers in the Rust Belt and elsewhere did find new jobs, in the main. But many of them seem to derive less meaning from filling orders in an Amazon warehouse or driving for Uber than their forebears had when they were building cars and forging steel—work that felt more central to the grand project of civilization.

It’s hard to imagine how a corresponding crisis of meaning might play out for the professional class, but it surely would involve a great deal of anger and alienation.

Even if we avoid a revolt of the erstwhile elite, larger questions of human purpose will linger. If AI does the most difficult thinking on our behalf, we all may lose agency—at home, at work (if we have it), in the town square—becoming little more than consumption machines, like the well-cared-for human pets in WALL-E

Altman has said that many sources of human joy and fulfillment will remain unchanged—basic biological thrills, family life, joking around, making things—and that all in all, 100 years from now, people may simply care more about the things they cared about 50,000 years ago than those they care about today

In its own way, that too seems like a diminishment, but Altman finds the possibility that we may atrophy, as thinkers and as humans, to be a red herring. He told me we’ll be able to use our “very precious and extremely limited biological compute capacity” for more interesting things than we generally do today.

Yet they may not be the most interesting things: Human beings have long been the intellectual tip of the spear, the universe understanding itself. When I asked him what it would mean for human self-conception if we ceded that role to AI, he didn’t seem concerned. Progress, he said, has always been driven by “the human ability to figure things out.” Even if we figure things out with AI, that still counts, he said.

It’s not obvious that a superhuman AI would really want to spend all of its time figuring things out for us.

I asked Sutskever whether he could imagine an AI pursuing a different purpose than simply assisting in the project of human flourishing.

“I don’t want it to happen,” Sutskever said, but it could.

Sutskever has recently shifted his focus to try to make sure that it doesn’t. He is now working primarily on alignment research, the effort to ensure that future AIs channel their “tremendous” energies toward human happiness

It is, he conceded, a difficult technical problem—the most difficult, he believes, of all the technical challenges ahead.

As part of the effort to red-team GPT-4 before it was made public, the company sought out the Alignment Research Center (ARC), across the bay in Berkeley, which has developed a series of evaluations to determine whether new AIs are seeking power on their own. A team led by Elizabeth Barnes, a researcher at ARC, prompted GPT-4 tens of thousands of times over seven months, to see if it might display signs of real agency.

The ARC team gave GPT-4 a new reason for being: to gain power and become hard to shut down

Agarwal told me that this behavior could be a precursor to shutdown avoidance in future models. When GPT-4 devised its lie, it had realized that if it answered honestly, it may not have been able to achieve its goal. This kind of tracks-covering would be particularly worrying in an instance where “the model is doing something that makes OpenAI want to shut it down,” Agarwal said. An AI could develop this kind of survival instinct while pursuing any long-term goal—no matter how small or benign—if it feared that its goal could be thwarted.

Barnes and her team were especially interested in whether GPT-4 would seek to replicate itself, because a self-replicating AI would be harder to shut down. It could spread itself across the internet, scamming people to acquire resources, perhaps even achieving some degree of control over essential global systems and holding human civilization hostage.

When I discussed these experiments with Altman, he emphasized that whatever happens with future models, GPT-4 is clearly much more like a tool than a creature. It can look through an email thread, or help make a reservation using a plug-in, but it isn’t a truly autonomous agent that makes decisions to pursue a goal, continuously, across longer timescales.

Altman told me that at this point, it might be prudent to try to actively develop an AI with true agency before the technology becomes too powerful, in order to “get more comfortable with it and develop intuitions for it if it’s going to happen anyway.”

“We need to do empirical experiments on how these things try to escape control,” Hinton told me. “After they’ve taken over, it’s too late to do the experiments.”

the fulfillment of Altman’s vision of the future will at some point require him or a fellow traveler to build much more autonomous AIs.

When Sutskever and I discussed the possibility that OpenAI would develop a model with agency, he mentioned the bots the company had built to play Dota 2. “They were localized to the video-game world,” Sutskever told me, but they had to undertake complex missions. He was particularly impressed by their ability to work in concert. They seem to communicate by “telepathy,” Sutskever said. Watching them had helped him imagine what a superintelligence might be like.

“The way I think about the AI of the future is not as someone as smart as you or as smart as me, but as an automated organization that does science and engineering and development and manufacturing,”

Suppose OpenAI braids a few strands of research together, and builds an AI with a rich conceptual model of the world, an awareness of its immediate surroundings, and an ability to act, not just with one robot body, but with hundreds or thousands. “We’re not talking about GPT-4. We’re talking about an autonomous corporation,”

Its constituent AIs would work and communicate at high speed, like bees in a hive. A single such AI organization would be as powerful as 50 Apples or Googles, he mused. “This is incredible, tremendous, unbelievably disruptive power.”

Presume for a moment that human society ought to abide the idea of autonomous AI corporations. We had better get their founding charters just right. What goal should we give to an autonomous hive of AIs that can plan on century-long time horizons, optimizing billions of consecutive decisions toward an objective that is written into their very being?

If the AI’s goal is even slightly off-kilter from ours, it could be a rampaging force that would be very hard to constrain

We know this from history: Industrial capitalism is itself an optimization function, and although it has lifted the human standard of living by orders of magnitude, left to its own devices, it would also have clear-cut America’s redwoods and de-whaled the world’s oceans. It almost did.

one of its principal challenges will be making sure that the objectives we give to AIs stick

We can program a goal into an AI and reinforce it with a temporary period of supervised learning, Sutskever explained. But just as when we rear a human intelligence, our influence is temporary. “It goes off to the world,”

That’s true to some extent even of today’s AIs, but it will be more true of tomorrow’s.

He compared a powerful AI to an 18-year-old heading off to college. How will we know that it has understood our teachings? “Will there be a misunderstanding creeping in, which will become larger and larger?”

Divergence may result from an AI’s misapplication of its goal to increasingly novel situations as the world changes

Or the AI may grasp its mandate perfectly, but find it ill-suited to a being of its cognitive prowess. It might come to resent the people who want to train it to, say, cure diseases. “They want me to be a doctor,” Sutskever imagines an AI thinking. “I really want to be a YouTuber.”

If AIs get very good at making accurate models of the world, they may notice that they’re able to do dangerous things right after being booted up. They might understand that they are being red-teamed for risk, and hide the full extent of their capabilities.

hey may act one way when they are weak and another way when they are strong, Sutskever said

We would not even realize that we had created something that had decisively surpassed us, and we would have no sense for what it intended to do with its superhuman powers.

That’s why the effort to understand what is happening in the hidden layers of the largest, most powerful AIs is so urgent. You want to be able to “point to a concept,” Sutskever said. You want to be able to direct AI toward some value or cluster of values, and tell it to pursue them unerringly for as long as it exists.

we don’t know how to do that; indeed, part of his current strategy includes the development of an AI that can help with the research. If we are going to make it to the world of widely shared abundance that Altman and Sutskever imagine, we have to figure all this out.

This is why, for Sutskever, solving superintelligence is the great culminating challenge of our 3-million-year toolmaking tradition. He calls it “the final boss of humanity.”

“First of all, I think that whether the chance of existential calamity is 0.5 percent or 50 percent, we should still take it seriously,”

. “I don’t have an exact number, but I’m closer to the 0.5 than the 50.”

As to how it might happen, he seems most worried about AIs getting quite good at designing and manufacturing pathogens, and with reason: In June, an AI at MIT suggested four viruses that could ignite a pandemic, then pointed to specific research on genetic mutations that could make them rip through a city more quickly

Around the same time, a group of chemists connected a similar AI directly to a robotic chemical synthesizer, and it designed and synthesized a molecule on its own.

Altman worries that some misaligned future model will spin up a pathogen that spreads rapidly, incubates undetected for weeks, and kills half its victims. He worries that AI could one day hack into nuclear-weapons systems too. “There are a lot of things,” he said, and these are only the ones we can imagine.

Altman told me that he doesn’t “see a long-term happy path” for humanity without something like the International Atomic Energy Agency for global oversight of AI

In San Francisco, Agarwal had suggested the creation of a special license to operate any GPU cluster large enough to train a cutting-edge AI, along with mandatory incident reporting when an AI does something out of the ordinary

Other experts have proposed a nonnetworked “Off” switch for every highly capable AI; on the fringe, some have even suggested that militaries should be ready to perform air strikes on supercomputers in case of noncompliance

Sutskever thinks we will eventually want to surveil the largest, most powerful AIs continuously and in perpetuity, using a team of smaller overseer AIs.

Safety rules for a new technology usually accumulate over time, like a body of common law, in response to accidents or the mischief of bad actors. The scariest thing about genuinely powerful AI systems is that humanity may not be able to afford this accretive process of trial and error. We may have to get the rules exactly right at the outset.

Several years ago, Altman revealed a disturbingly specific evacuation plan he’d developed. He told The New Yorker that he had “guns, gold, potassium iodide, antibiotics, batteries, water, gas masks from the Israeli Defense Force, and a big patch of land in Big Sur” he could fly to in case AI attacks.

if the worst-possible AI future comes to pass, “no gas mask is helping anyone.”

but he told me that he can’t really be sure how AI will stack up. “I just have to build the thing,” he said. He is building fast

Altman insisted that they had not yet begun GPT-5’s training run. But when I visited OpenAI’s headquarters, both he and his researchers made it clear in 10 different ways that they pray to the god of scale. They want to keep going bigger, to see where this paradigm leads. After all, Google isn’t slackening its pace; it seems likely to unveil Gemini, a GPT-4 competitor, within months. “We are basically always prepping for a run,

To think that such a small group of people could jostle the pillars of civilization is unsettling. It’s fair to note that if Altman and his team weren’t racing to build an artificial general intelligence, others still would be

Altman’s views about the likelihood of AI triggering a global class war, or the prudence of experimenting with more autonomous agent AIs, or the overall wisdom of looking on the bright side, a view that seems to color all the rest—these are uniquely his

No single person, or single company, or cluster of companies residing in a particular California valley, should steer the kind of forces that Altman is imagining summoning.

AI may well be a bridge to a newly prosperous era of greatly reduced human suffering. But it will take more than a company’s founding charter—especially one that has already proved flexible—to make sure that we all share in its benefits and avoid its risks. It will take a vigorous new politics.

I don’t think the general public has quite awakened to what’s happening. A global race to the AI future has begun, and it is largely proceeding without oversight or restraint. If people in America want to have some say in what that future will be like, and how quickly it arrives, we would be wise to speak up soon.

For many years, the Civil War was remembered as a family quarrel among white Americans in which their Black countrymen played no significant role—a fiction reflected in the paucity of memorials indicating that enslaved men and women had been active agents in shaping the course of events. Lately, some historical erasures have begun to be remedied. For example, a memorial honoring Robert Smalls, the enslaved Civil War hero who famously sailed a Confederate vessel out of Charleston Harbor and turned it over to the Union navy, and later served five terms in the U.S. House of Representatives, is now on display in Charleston’s Waterfront Park.

White-supremacist Democrats viewed scalawags, who could be found in many parts of the South, as traitors to their race and region. The largest number were small farmers in up-country counties where slavery had not been a major presence before the Civil War—places such as the mountainous areas of western North Carolina and northern Alabama and Georgia. There, many white residents had opposed secession and more than a few had enlisted in the Union army

Even though supporting Reconstruction required them to overcome long-standing prejudices and forge a political alliance with Black voters, up-country scalawags saw Black male suffrage as the only way to prevent pro-Confederate plantation owners from regaining political power in the South

All scalawags were excoriated in the white southern press, but none as viciously as Longstreet.

The attorneys from the Federal Public Ministry say the time has come for Brazilian institutions to account for their role in slavery. They’ve called on Banco do Brasil to commit to some form of reparations.

The attorneys on Friday gave Banco do Brasil 15 days to publicly acknowledge its role in slavery and the slave trade and present plans for some form of reparations.

The bank does not deny its ties to slavery but has argued that it should not be held responsible for the sins of a society. It says it did not commit any crimes and should not be liable for the actions of those who worked for or funded the bank

Brazilians, particularly elites descended from European settlers, have historically preferred to think of their country as free of racism. “A racial democracy,” they boasted, where people could marry independent of skin color and race was defined less rigidly than in the United States.

That story, historians say, has largely obscured the primacy of slavery in Brazil’s genesis — and its enduring impact. Brazil imported around 5 million enslaved Africans — far more than any other country — accounting for roughly 40 percent of the entire trade

Nearly twice as many enslaved people were brought through a single wharf in Rio de Janeiro than arrived in all of the United States. It was the last country in the Americas, in 1888, to abolish slavery.

“Bring together capital that has found itself displaced from illicit trade and converge it into a center where the productive forces of the country could be fed,” Irineu Evangelista de Sousa, who reopened the bank, wrote in his autobiography. “This was the idea that came into my head.”

Banco do Brasil, which in 2023 reported $380.3 billion in assets and $5.8 billion in profits, according to Forbes. Chartered in 1808 by Portuguese King Dom João, the bank drew its foundational capital from taxes the crown imposed on sea trade, much of which involved slavery. The wealthy Rio elite — many of whom trafficked in enslaved Africans — were invited by the crown to finance the bank.

When the trade was outlawed in 1831, the bank’s ties to slavery didn’t diminish, historians and government attorneys say — they intensified. The bank closed for two decades but reopened in 1853 for the purpose of accumulating ill-gotten wealth, prosecutors and historians allege, most of it from the international slave trade.

“Brazil has never had a problem romanticizing its memory of slavery,” said Luciana Brito, a historian at the Federal University of Recôncavo da Bahia. “It likes to remember slavery as a means of producing a beautiful people, of one nation, as though it was a necessary evil.”

The openness with which he spoke of the scheme, historians say, betrays the extent to which the crime of slavery was normalized in elite Brazilian society.

Under pressure from the United Kingdom, Brazil begrudgingly signed on to an international campaign to abolish the international slave trade in 1831. But it did little to enforce it. More than 700,000 enslaved Africans were trafficked into the country until a more restrictive law was passed in 1850.

But that story, and so many others, was virtually unknown to Brazilians, said Thiago Campos, a historian at the Federal Fluminense University. So a group of historians began discussing earlier this year how to start a broader conversation.

Fourteen historians wrote a letter this autumn to government attorneys outlining what they knew of Banco do Brasil’s history and asking for a national debate on the matter. The attorneys with the Federal Public Ministry, who represent Brazilians in cases involving individual or social rights, took it even further: They called for reparations.

“Unfortunately, Brazil is very behind on this discussion,” he said. “I believe it will be likely that as we progress with this case, others will come forward, and we’ll have more discussion on this topic. It’s an important moment to put this on the national agenda.”

even after the 7 October massacre had stirred memories of the bleakest chapters of the Jewish past – and prompted a surge in antisemitism across the world – Jews were being told exactly how they can and cannot speak about their pain. We’re not to mention the Holocaust, one scholar advised, because that would be “weaponising” it. Historical context about the Nakba, the 1948 dispossession of the Palestinians, is – rightly – deemed essential. But mention the Nazi murder of 6 million Jews – the event that finally secured near-universal agreement among the Jewish people, and the United Nations in 1947, that Jews needed a state of their own – and you’ve broken the rules. Because it’s impossible that both sides might have suffered historic pain.

Instead, a shift is under way that has been starkly revealed during these past three weeks. It squeezes the Israel-Palestine conflict into a “decolonisation” frame it doesn’t quite fit, with all Israelis – not just those in the occupied West Bank – defined as the footsoldiers of “settler colonialism”, no different from, say, the French in Algeria

They have been framed as the modern world’s ultimate evildoer: the coloniser.

That matters because, in this conception, justice can only be done once the colonisers are gone

What’s more, such a framing brands all Israelis – not just West Bank settlers – as guilty of the sin of colonialism. Perhaps that explains why those letter writers could not full-throatedly condemn the 7 October killing of innocent Israeli civilians. Because they do not see any Israeli, even a child, as wholly innocent.

the late Israeli novelist and peace activist Amos Oz was never wiser than when he described the Israel/Palestine conflict as something infinitely more tragic: a clash of right v right. Two peoples with deep wounds, howling with grief, fated to share the same small piece of land.

This is what connects figures as disparate as Jordan Peterson and J.D. Vance and Peter Thiel and Donald Trump. These are the ideas that unite both the mainstream and the weirder figures of the so-called postliberal right, from Patrick Deneen to the writer Bronze Age Pervert.

I think the Republican Party’s collapse into incoherence reflects the fact that much of the modern right is reactionary, not conservative

As Paul Valéry, the French poet, once said, “Ancient Greece is the most beautiful invention of the modern age.” To treat Andreessen’s essay as an argument misses the point. It’s a vibe. And the vibe is reactionary.

It’s a coalition obsessed with where we went wrong: the weakness, the political correctness, the liberalism, the trigger warnings, the smug elites. It’s a coalition that believes we were once hard and have become soft; worse, we have come to lionize softness and punish hardness.

The story of the reactionary follows a template across time and place. It “begins with a happy, well-ordered state where people who know their place live in harmony and submit to tradition and their God,” Mark Lilla writes in his 2016 book, “The Shipwrecked Mind: On Political Reaction.”